Assessment of Blasting Vibration Velocity of Large-Span Underground Railway Station Based on Micro-Seismic Monitoring

Fang, Qian (Beijing Jiaotong University) | Li, Ao (Beijing Jiaotong University) | Zhong, Yue (Beijing Jiaotong University) | Liu, Yan (Beijing Jiaotong University) | Zhang, Dingli (Beijing Jiaotong University)



Blasting operation is one of the most efficient techniques for rock breakage in tunnel engineering. Meanwhile blasting energy is dissipated through the ground which may produce some negative effects, such as ground vibration, flyrock, explosive noise, and air blast pressure. Ground vibration is one of the most undesirable effects induced by blasting operation in mountain tunnels which could cause negative impacts on the residents living nearby and adjacent structures. The correlation between the structural vibration and the vibration velocity of particles is more closely related than that between the displacement and the acceleration. Therefore the ground vibration effects can be well represented by peak particle velocity (PPV) on the ground.

In this research, we use the microseismic monitoring technique to observe the PPV of the mountain surface, below which the Badaling Great Wall Railway Station is constructed. The maximum excavation span of the station reaches 32.7m and is excavated below the Great Wall. A total of 53 sets of monitoring results of the station caused by blasting inside the station are collected. The monitoring results include the PPV, the blasting charge, the distance from blasting point to ground surface, and the moment magnitude. The effects of the blasting energy, the rockmass condition, and the geological topography on the PPV are studied. Regression analysis are also conducted to relate PPV to associated parameters. The obtained relationship can be used to predict the responses of the Great Wall due to blast inside the station. Moreover, we can use the research results to determine the proper blasting charge of station excavation.

1. Introduction

When a mountain tunnel is excavated using the drilling and blasting method, the vibration due to blast inevitably produces negative impacts on the surface structures (Ak et al., 2009; Nateghi, 2012; Verma et al., 2018). The appropriate evaluation of the blasting vibration is of fundamental importance in safeguarding the existing structures adjacent to tunnelling. The peak particle velocity (PPV) is the key parameter, commonly adopted to identify the blasting vibration impacts on existing structures (Hasanipanah et al., 2017).Peak particle velocity refers to the maximum speed of a particular particle as it oscillates about a point of equilibrium that is moved by a passing wave, which is proportional to the produced energy and dynamic stress due to blasting (Faradonbeh et al., 2016). The PPV is one of the best single descriptor for correlating case history data with vibration-induced damage (New, 1986; Sharif, 2000). Both the analytical solutions (Sambuelli, 2009; Arora and Dey, 2010) and empirical solutions (Jiang and Zhou, 2012; Xia et al., 2018) have been proposed to calculate the PPV produced by blast. Numerical simulations (Saiang and Nordlund, 2009; Verma et al., 2018) have also been used to obtain the PPV associated with blast. In addition, the artificial intelligence methods, including artificial neural networks, genetic algorithms, and fuzzy expert systems have been conducted to predict the PPV value (Dehghani and Ataee-Pour, 2011; Monjezi et al., 2011; Amnieh et al., 2012; Faradonbeh et al., 2016).